Christian Wuerslin

Hi Yan,

great code. I have one suggestion though: In your CV reinit process, you implemented a very efficient distance transform. However, for performance reasons, you don't compute the values for the edges of the matrix (always 0). Thus I would suggest, you pad the input matrix with 0s and then un-pad the output matrix of this step:

u0 = y_binary_boundary_detection(uint8(u>0));
u0 = padarray(u0, [1 1 1]); % padding
u0 = ac_distance_transform_3d(u0);
u0 = u0(2:end-1, 2:end-1, 2:end-1); % un-padding
u = u0.*sign(u);

Cheers, Christian

Hi Jiro,

OK, I think I'm starting to get the idea of the difference between app and function :). So the next version of the app will simply return the figure handle to comply with the specs.

Thanks for the publicity <3

Hi Chris,

actually there is nothing really new in this algorithm. I only decided to trade a little bit of accuracy for a lot of speed. This is done by using the differen queues which can be regarded as intensity difference bins. I saw a similar approach in a paper by Johan Berglund (2010 in "Magn Reson Imaging") in a slightly differen context, however, I do not know whether he came up with it himself.

Christian

Nice work Christian. Did you develop the algorithm yourself? Will it appear as a published article?
Chris W

buen material